A very simple model for predicting thermal conductivity based on its definiensis was presented. The thermal conductivity obtained using the model provided a good coincidence to the investigations performed by other authors. The heat transfer coefficient was determined by inverse analysis using the temperature measurements. From experimental results, it is noted that heat transfer coeffi cient increases with the increase of wind velocity and relative humidity, a prediction equation on heat transfer coeffi cient about wind velocity and relative humidity is given.

This paper aims to detect climate change points and compare the extreme temperature changes with the average-value changes in the Amur River basin. The daily air temperatures of 44 stations in the Amur River basin were collected from April 1, 1954, to March 31, 2013. The change points for annual mean and extreme temperature in 44 individual stations and their average were detected by the Mann-Kendall test, respectively. The annual mean temperature changed during 1980s in terms of increased mean value and relative stable standard deviation. The annual maximum temperature from 31 stations mostly located in the central and northwest basin changed significantly, and their change points occurred mainly in 1990s. For the annual minimum temperature, 32 stations mainly located in the central basin had significant changes. The generalized extreme value distribution was fitted to the postchange point subseries of annual extreme temperature and the parameters were estimated by the maximum likelihood method. The 10/50/100-year return levels were estimated by the method of profile likelihood. For the areas in the central and Northwestern basin, the probability of occurrence of hot extremes increased, while the occurrence probability of cold extremes was decreased in the central basin under climate change.

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The histogram comparison approach (HCA) is proposed to assess the alteration of hydrologic regimes, which are characterized by the hydrologic metrics, for example, the indicators of hydrologic alteration. The HCA method considers alterations within the whole range of the hydrologic regime and estimates the alteration degree by comparing the pre‐impact and post‐impact histograms. A key parameter of the HCA method is the similarity degree, which considers both the class‐by‐class and cross‐class information of histograms and reflects how many features of the pre‐impact histogram remain in the post‐impact histogram. The alteration degree is defined as the mathematical maximum similarity degree, that is, 100%, subtracted by the actual similarity degree in the HCA method. Comparing the HCA method to the existing range of variability approach and histogram matching approach through theoretical analysis and case studies, the HCA method can eliminate some limitations of the range of variability approach and histogram matching approach methods and can more accurately and effectively assess the hydrologic regime alteration. The Ob and Yangtze Rivers, which are located in different climatic zones, are used as case studies. Hydrologic regime alterations impacted by reservoirs with different regulation abilities (daily, seasonally and yearly) were assessed using the HCA method, the results of which verified its rationality and practicability. More sites with a wider range of flow variations will be examined in the future to assess the applicability of the HCA method. Copyright © 2017 John Wiley & Sons, Ltd.